Module 13

Measuring Agent Success

Metrics, evaluation, and monitoring

TL;DR

Metrics, evaluation, and monitoring

> Overview

Traditional metrics (page views, click rates) do not capture agent quality. You need new metrics: task completion rate, hallucination rate, user satisfaction with agent output, cost per task, and latency percentiles. This module teaches PMs how to build an agent metrics dashboard, implement automated evaluation, and detect quality degradation.

> Why This Matters for Your Product

If you cannot measure it, you cannot improve it and you cannot justify investment to stakeholders. Agent quality is subjective and probabilistic: the same prompt might produce different results. You need automated evaluation pipelines that continuously score your agent's output, detect quality degradation, and alert when performance drops. This is how you build stakeholder confidence.

> Interactive & tools

Metrics dashboard (example)

Agent metrics dashboard (example)

Task completion rate

94%

Quality score (LLM-as-Judge)

4.2/5

Hallucination rate

1.2%

Cost per task

$0.012

Latency P95

8.2s

Escalation rate

5%

Core metrics: completion rate, quality score, hallucination rate, cost per task, latency P50/P95, CSAT, escalation rate, error rate.

Eval flywheel

The eval flywheel

ProductionFailuresTest casesBetter agentMore usageEdge casesBetter evals

Every production failure becomes a test case. Better evals → better agent → more trust → more usage → more edge cases → better evals.

Related Engineering Patterns

These are the technical patterns your engineering team will implement. Understanding them helps you have better conversations.

Evaluation & MonitoringGoal Setting & Monitoring

See the full decision framework

Sign up free to see this module's Key Decisions, the questions to ask your engineering team, and play the interactive Measuring Agent Success game.

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